Dataset Information

A Candidate Prognostic Biomarker Complement Factor I Promotes Malignant Progression in Glioma.

ABSTRACT: Objectives: Glioma is the most common and aggressive type of primary central nervous system (CNS) tumor in adults and is associated with substantial mortality rates. The aim of our study was to evaluate the prognostic significance and function of the complement factor I (CFI) in glioma. Materials and Methods: The expression levels of CFI in glioma tissues and the survival of the CFI^high and CFI^low patient groups were analyzed using The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). The correlation between CFI expression and clinicopathological features of glioma was determined by univariate and multivariate Cox regression analyses in the Chinese Glioma Genome Atlas (CGGA) database. The functional role of CFI in glioma was established through routine in vitro and in vivo assays. Results: CFI is overexpressed in glioma and its high levels correlated with poor outcomes in both TCGA and CGGA datasets. Furthermore, CFI was identified as an independent prognostic factor of glioma in the CGGA database. CFI knockdown in glioma cell lines inhibited growth in vitro and in vivo, whereas its ectopic expression increased glioma cell proliferation, migration, and invasion in vitro. CFI protein levels were also significantly higher in the glioma tissues resected from patients and correlated to worse prognosis. Conclusions: CFI is a potential prognostic biomarker in glioma and drives malignant progression.

SUBMITTER: Cai X

PROVIDER: S-EPMC7889977 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Candidate Prognostic Biomarker Complement Factor I Promotes Malignant Progression in Glioma.

Cai Xiaomin X Qiu Wenjin W Qian Mengshu M Feng Shuang S Peng Chenghao C Zhang Jiale J Wang Yi Y Wang Yuhai Y

Frontiers in cell and developmental biology 20210204

Objectives: Glioma is the most common and aggressive type of primary central nervous system (CNS) tumor in adults and is associated with substantial mortality rates. The aim of our study was to evaluate the prognostic significance and function of the complement factor I (CFI) in glioma. Materials and Methods: The expression levels of CFI in glioma tissues and the survival of the CFIhigh and CFIlow patient groups were analyzed using The Cancer Genome Atlas (TCG ...[more]

PMID: 33614625

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Project description:BackgroundRGS protein family members have recently became new potentially promising therapeutic targets in many cancers. However, as a key member of RGS family, RGS16 has seldom been studied in glioma. The present study was designed to investigate the prognostic value and biological function of RGS16 based on large-scale databases and functional assays in vitro.MethodsHere, we performed comprehensive analysis for the expression characteristic of RGS16 in Chinese Glioma Genome Atlas (CGGA) microarray database with 301 patients and validated in The Cancer Genome Atlas (TCGA) microarray and RNA sequencing database. Student's t-test, one-way ANOVA test and long-rank test were used to assess differences between groups. Kaplan-Meier survival, univariate and multivariate Cox analysis and ROC curve were used to estimate the survival distributions. Biological implication of abnormal expression of RGS16 in glioma was also explored. Functional analysis of RGS16 was performed in several glioblastoma (GBM) cell lines. R language and SPSS were used for statistical analysis and graphical work.ResultsWe found that the expression of RGS16 was positively related to the grade of glioma. High level of RGS16 commonly gathered in glioma of mesenchymal subtype and wild-type IDH1. Moreover, higher expression level of RGS16 was found to be significantly correlated with poor prognosis. The univariate and multivariate Cox regression analysis and ROC curve showed that RGS16 was an independent prognostic factor for glioma patients. Gene ontology analysis, gene set enrichment analysis, and gene set variation analysis suggested that the overexpression of RGS16 tightly related to cell proliferation, migration, epithelial-mesenchymal transition (EMT), immune and inflammatory response of glioma. Knockdown of RGS16 in glioma cell lines also showed that RGS16 promoted the malignant progress of glioma cell lines.ConclusionsRGS16 plays an important role in glioma progression and serves as an independent prognostic factor, especially in GBM patients.

Project description:BackgroundGlioma is one of the most common malignancies in the central nervous system and has limited effective therapeutic options. Therefore, we sought to identify a suitable target for immunotherapy.Materials and methodsWe screened prognostic genes for glioma in the CGGA database and GSE43378 dataset using survival analysis, receiver operating characteristic (ROC) curves, independent prognostic analysis, and clinical correlation analysis. The results were intersected with immune genes from the ImmPort database through Venn diagrams to obtain likely target genes. The target genes were validated as prognostically relevant immune genes for glioma using survival, ROC curve, independent prognostic, and clinical correlation analyses in samples from the CGGA database and GSE43378 dataset, respectively. We also constructed a nomogram using statistically significant glioma prognostic factors in the CGGA samples and verified their sensitivity and specificity with ROC curves. The functions, pathways, and co-expression-related genes for the glioma target genes were assessed using PPI networks, enrichment analysis, and correlation analysis. The correlation between target gene expression and immune cell infiltration in glioma and the relationship with the survival of glioma patients were investigated using the TIMER database. Finally, target gene expression in normal brain, low-grade glioma, and high-grade glioma tissues was detected using immunohistochemical staining.ResultsWe identified TNFRSF12A as the target gene. Satisfactory results from survival, ROC curve, independent prognosis, and clinical correlation analyses in the CGGA and GSE43378 samples verified that TNFRSF12A was significantly associated with the prognosis of glioma patients. A nomogram was constructed using glioma prognostic correlates, including TNFRSF12A expression, primary-recurrent-secondary (PRS) type, grade, age, chemotherapy, IDH mutation, and 1p19q co-deletion in CGGA samples with an AUC value of 0.860, which illustrated the accuracy of the prognosis prediction. The results of the TIMER analysis validated the significant correlation of TNFRSF12A with immune cell infiltration and glioma survival. The immunohistochemical staining results verified the progressive up-regulation of TNFRSF12A expression in normal brain, low-grade glioma, and high-grade glioma tissues.ConclusionWe concluded that TNFRSF12A was a viable prognostic biomarker and a potential immunotherapeutic target for glioma.

Project description:Objective: Brain tumors (gliomas) contain large populations of infiltrating macrophages and recruited microglia, which in experimental murine glioma models promote tumor formation and progression. Among the barriers to understanding the contributions of these stromal elements to high-grade glioma (glioblastoma; GBM) biology is the relative paucity of tools to characterize infiltrating macrophages and resident microglia. In this study, we leveraged multiple RNA analysis platforms to identify new monocyte markers relevant to GBM patient outcome. Methods: High-confidence lists of mouse resident microglia- and bone marrow-derived macrophage-specific transcripts were generated using converging RNA-seq and microarray technologies and validated using qRT-PCR and flow cytometry. Expression of select cell surface markers was analyzed in brain-infiltrating macrophages and resident microglia in an induced GBM mouse model, while allogeneic bone marrow transplantation was performed to trace the origins of infiltrating and resident macrophages. Glioma tissue microarrays were examined by immunohistochemistry, and the Gene Expression Omnibus (GEO) database was queried to determine the prognostic value of identified microglia biomarkers in human GBM. Results: We generated a unique catalog of differentially-expressed bone marrow-derived monocyte and resident microglia transcripts, and demonstrated that brain-infiltrating macrophages acquire F11R expression in GBM and following bone-marrow transplantation. Moreover, mononuclear cell F11R expression positively correlates with human high-grade glioma and additionally serves as a biomarker for GBM patient survival, regardless of GBM molecular subtype. Significance: These studies establish F11R as a novel monocyte prognostic marker for GBM critical for defining a subpopulation of stromal cells for future potential therapeutic intervention. Total RNA was isolated from three independently-generated sets of flow sorted bone marrow monocytes (CD11b+ CD45high CD115+ Ly6G- cells) and brainstem microglia (CD11b+ CD45low CD115low Ly6G- cells) for Illumina RNA-Seq, and two additional pools were subsequently generated and submitted for Affymetrix Mouse Exon 1.0ST microarray. Two of the RNA-Seq samples were additionally analyzed by the microarray, for a total of 6 samples (3 monocyte, 3 microglia) in each platform. Data outputs were analyzed by two analysis methods each (RNA-Seq data: ALEXA-Seq and Cufflinks; microarray data: Partek and Aroma). All four lists were merged into a new high-confidence gene list of transcripts that were significantly differentially expressed (DE) in three out of the four analyses. In this dataset, we includeRNA-Seq data obtained from flow sorted mouse bone marrow monocytes and brainstem microglia.

Project description:Objective: Brain tumors (gliomas) contain large populations of infiltrating macrophages and recruited microglia, which in experimental murine glioma models promote tumor formation and progression. Among the barriers to understanding the contributions of these stromal elements to high-grade glioma (glioblastoma; GBM) biology is the relative paucity of tools to characterize infiltrating macrophages and resident microglia. In this study, we leveraged multiple RNA analysis platforms to identify new monocyte markers relevant to GBM patient outcome. Methods: High-confidence lists of mouse resident microglia- and bone marrow-derived macrophage-specific transcripts were generated using converging RNA-seq and microarray technologies and validated using qRT-PCR and flow cytometry. Expression of select cell surface markers was analyzed in brain-infiltrating macrophages and resident microglia in an induced GBM mouse model, while allogeneic bone marrow transplantation was performed to trace the origins of infiltrating and resident macrophages. Glioma tissue microarrays were examined by immunohistochemistry, and the Gene Expression Omnibus (GEO) database was queried to determine the prognostic value of identified microglia biomarkers in human GBM. Results: We generated a unique catalog of differentially-expressed bone marrow-derived monocyte and resident microglia transcripts, and demonstrated that brain-infiltrating macrophages acquire F11R expression in GBM and following bone-marrow transplantation. Moreover, mononuclear cell F11R expression positively correlates with human high-grade glioma and additionally serves as a biomarker for GBM patient survival, regardless of GBM molecular subtype. Significance: These studies establish F11R as a novel monocyte prognostic marker for GBM critical for defining a subpopulation of stromal cells for future potential therapeutic intervention. Total RNA was isolated from three independently-generated sets of flow sorted bone marrow monocytes (CD11b+ CD45high CD115+ Ly6G- cells) and brainstem microglia (CD11b+ CD45low CD115low Ly6G- cells) for Illumina RNA-Seq, and two additional pools were subsequently generated and submitted for Affymetrix Mouse Exon 1.0ST microarray. Two of the RNA-Seq samples were additionally analyzed by the microarray, for a total of 6 samples (3 monocyte, 3 microglia) in each platform. Data outputs were analyzed by two analysis methods each (RNA-Seq data: ALEXA-Seq and Cufflinks; microarray data: Partek and Aroma). All four lists were merged into a new high-confidence gene list of transcripts that were significantly differentially expressed (DE) in three out of the four analyses. In this dataset, we include exon expression data obtained from flow sorted mouse bone marrow monocytes and brainstem microglia.

Dataset Information

A Candidate Prognostic Biomarker Complement Factor I Promotes Malignant Progression in Glioma.

Publications

A Candidate Prognostic Biomarker Complement Factor I Promotes Malignant Progression in Glioma.

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